Optimal transport (OT) is a method for mapping one probability
distribution into another. OT also leads to a method for defining a
geodesic between distributions which allows us to morph one
distribution into another. I will introduce the basics of optimal
transport and I will explain how optimal transport maps and
morphings can be estimated from data.
In this lecture, I will provide an introduction to Gaussian
processes (GPs), with a view toward applications in high-energy
physics. I will start with the basic definition of a GP and explain
how to perform inference with these models. I will then describe
the choice and estimation of the mean and the covariance
function and demonstrate these ideas with simple examples.
I will...
In this lecture I will discuss a method of morphing distributions
that is useful to measure the parameters of an Effective Field
Theory (EFT). I will introduce EFT which is a powerful
theoretical framework that is used to systematically extend
known physics lagrangians. I will then talk about the idea
behind the morphing between distributions given the
predictions at some point in the...
